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Full-Time

Machine Learning Engineer

Product

Confirmed live in the last 24 hours

PhysicsX

PhysicsX

51-200 employees

AI-driven simulation for advanced industries

Hardware
Industrial & Manufacturing
Energy
Enterprise Software
AI & Machine Learning
Aerospace

Junior, Mid

London, UK

Category
Applied Machine Learning
Deep Learning
AI & Machine Learning
Required Skills
Python
Tensorflow
Pytorch
Docker
Requirements
  • 2+ years’ experience in a product engineering role, with exposure to implementing python libraries using OOP principles
  • Experience applying DL or NN model architectures to geometric data (e.g., graph neural networks)
  • Extensive experience with numerical and DL libraries (e.g., JAX and PyTorch)
  • Using distributed computing frameworks (e.g., Ray)
  • Docker for development and deployment
  • Excellent collaboration and communication skills - with teams and users
Responsibilities
  • Help shape some of our key product engineering areas – software development standards, frameworks, testing and release process
  • Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
  • Work closely with product management to identify new opportunities for the product engineering team
  • Design and develop python libraries that solve complex problems in applying machine learning to design and engineering
  • Write high-quality code that allow us to create scalable and reliable machine learning libraries
  • Use common libraries for 3D mesh data manipulation and deep learning such as PyVista, JAX, TensorFlow, PyTorch
  • Explore new techniques and frameworks to integrate into our tech stack (as technology evolves, we strive for making relevant changes on our stack when needed)

PhysicsX enhances the design and operation of machines in advanced industries using artificial intelligence and simulation technologies, focusing on sectors like renewable energy, healthcare, and transportation. The company provides AI-driven simulations that help clients, such as medical device manufacturers and aerospace firms, create more efficient designs and processes. Unlike competitors, PhysicsX offers specialized services on a project basis or through long-term contracts, leveraging its expertise in machine learning. The goal is to achieve engineering breakthroughs that positively impact climate and human health.

Company Stage

Series A

Total Funding

$32M

Headquarters

London, United Kingdom

Founded

N/A

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
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Simplify's Take

What believers are saying

  • Securing $32 million in Series A funding positions PhysicsX for accelerated growth and expansion in customer delivery and product development.
  • The addition of industry veterans like Jim Baum and Jeremy Palmer to the board enhances the company's strategic direction and operational expertise.
  • PhysicsX's technology has the potential to drive significant performance improvements in critical sectors such as healthcare, renewable energy, and transportation, making it a highly impactful place to work.

What critics are saying

  • The competitive landscape in AI and simulation engineering is intense, requiring PhysicsX to continuously innovate to maintain its edge.
  • Dependence on project-based revenue can lead to financial volatility, especially if client acquisition slows down.

What makes PhysicsX unique

  • PhysicsX leverages advanced AI-driven simulations specifically tailored for industries with significant climate and health impacts, setting it apart from general AI service providers.
  • The company's focus on project-based and long-term contracts allows for deep, customized engagements with clients, unlike competitors who may offer more generic solutions.
  • PhysicsX's leadership team, with extensive experience in machine learning and engineering, provides a strong foundation for innovation and client trust.